Technical note: Determination of proton linear energy transfer from the integral depth dose

Medical physics(2023)

引用 0|浏览7
暂无评分
摘要
Background Proton linear energy transfer (LET) is associated with the relative biological effectiveness of radiation on tissues. Monte Carlo (MC) simulations have been known to be the preferred method to calculate LET. Detectors have also been built to measure LET, but they need to be calibrated with MC simulations.Purpose To propose and test a MC-free method for determining LET from the measured integral depth dose (LFI) of the protons of interest.Method and materials LFI consists of three steps: (1) IDD measurements, (2) extraction of energy spectrum (ES) from the IDD, and (3) LET determination from the extracted ES and the stopping power of each energy. To validate the accuracy of the extraction of ES, we use Gaussian ES to synthesize IDD, extract ES from the synthesized IDD, and then compare the original (ground truth) and extracted ES. LETs calculated from the original and extracted ES are also compared. To obtain the LET of protons of interest, we measure IDDs by a large-area plane-parallel ionization chamber in water. Finally, TOPAS MC is employed to simulate IDDs, ES, and LETs. From the simulated IDD, the extracted ES and LET are compared with the simulations from TOPAS MC.Results From the synthesized IDDs, the LETs agreed excellently when the peak energies >= 10 and 1.25 MeV with depth resolutions 0.1 and 0.01 mm, respectively. For energy <1.25 MeV, even higher depth resolution than 0.01 mm is required. From the MC simulated IDDs, our track-averaged LET excellently agreed with MC simulation, but not the LETd. Our LETd was smaller than MC simulated LETd in the shallow region but larger in the distal Bragg peak region.Conclusion LET can be accurately determined from the IDD. This method can be used in the clinic to commission or validate LETs from other measurement methods or a treatment planning system.
更多
查看译文
关键词
energy spectrum,LET measurement,Monte-Carlo free,relative biological effectiveness
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要